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Record W2899696537 · doi:10.1073/pnas.1808035115

Peculiarly pleasant weather for US maize

2018· article· en· W2899696537 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2018
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCrop Yield and Soil Fertility
Canadian institutionsnot available
FundersU.S. Department of AgricultureDavid and Lucile Packard FoundationNational Science Foundation
KeywordsGrowing seasonSowingCropYield (engineering)Quarter (Canadian coin)Environmental scienceAgronomyAgricultureAgricultural economicsAgricultural engineeringGeographyBiologyEconomicsEngineeringEcology

Abstract

fetched live from OpenAlex

Significance Over the course of the 20th century, US maize yields have improved by more than a factor of five. Whereas this trend is often attributed exclusively to technological improvements, here, we also identify contributions from improved temperatures during the growing season. More than one-quarter of the increase in crop yield since 1981 is estimated to result from trends toward overall warmer conditions, but with cooling of the hottest growing-season temperatures, and from adjustments in crop timing toward earlier planting and longer maturation varieties.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.260

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.059
GPT teacher head0.292
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it